Abstract: Objective To explore the significance of combination of factor analysis and cluster a- nalysis in CT images classification of pulmonary tuberculosis and to provide a scientific basis for the criterion of classification.Methods The CT appearance images of 243 active pulmonary tuberculo- sis(PTB)cases were divided into 13 sorts,and analyzed by combination factor analysis(varimax) with cluster analysis.The value in diagnose smear positive and smear negative PTB was compared. Results CT findings of 243 cases can be induced into 5 common factors according to factor analysis, including air spreading factor,consolidation factor,centrilobular nodule positive factor,centrilobu- lar nodules negative factor and cavity factor.The images of the secondary PTB can be subdivided to 5 groups by K-mean cluster analysis,viz.cavity-air spread type 59 cases(24.3%),cavity type 34 cases(14.0%),air spread type 32 cases(13.2%),consolidation type 54 cases(22.2%)and centri- lobule nodule type 64 cases(26.3%).There was significant statistical difference in composition of classification between smear positive and negative cases(P<0.05).Among the total,cavity-air spread type and consolidation type in the smear positive cases were obviously more than those of negative cases,and while centrilobular nodule type in smear negative groups was vividly less than one of positive groups.Conclusions Combination between factor analysis and clustering analysis can reveal the characteristics and regularity of multiplex CT images of PTB,perform scientific clas-sification and improve the diagnosis of active PTB,especially smear negative cases.

Key words: Pulmonary tuberculosis, Factor analysis, Cluster analysis, Tomography,X-ray computed, diagnosis